discussion session -
TRANSCRIPT
Find out who’s working on bioinformatics at Miami
Find out who has tools and expertise at Miami that can be applied to bioinformatics research
Get biologists and non-biologists to talk to (and maybe even understand!) each other
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Two-hour session
Brief introduction of attendees Biologists – state research problems that desire
collaboration on
Non-biologists – give tools and expertise available for collaboration on bioinformatics/biology problems
Break up into informal discussion session, with facilitation by Chun Liang and Quinn Li, botany
Valerie Cross and John Karro, computer science
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Expertise in biostatistics Analysis of dose-related tumorigenic trends in the
presence of treatment-related toxicity Analysis of pharmacokinetic data, particularly,
methods for testing the equivalence of the areas under concentration-time profile curves
Risk assessment Inverse regression/calibration problems where the
dose associated with a particular level of response is estimated and tested
Optimal design of experiments for simple compartmental models
Integration of model uncertainty in the generation of risk estimates
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Analysis and optimization of algorithms
Interested in developing efficient algorithms for finding similar sequences in genomic databases
Work with problems that have well-defined measure of similarity or difference between objects
Improve problem solutions that currently use too much memory or take too much time
Edit distance (number of operations to change one text/genomic string to another)
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Study how insect viral genes (esp. baculovirusand ascovirus) are regulated in insect cells
Baculovirus – would like bioinformatic prediction of which AATAAA used in certain processing
Ascovirus – would like bioinformatic search for particular stem loop structure, which could then be verified in lab
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Ontology - a vocabulary that represents a set of concepts of a particular domain and the relationships between those concepts
Gene Ontology (GO) guarantees the consistency of the referenced biological concepts in different databases
Use to annotate genes in various databases
Annotations used to determine similarity between genes and gene products
Group has made various ontology software tools
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Primary focus on computationally-based analysis of DNA and RNA sequences
Develop tools to help with analysis
Example: Working on identification of functional genomic regions through comparison of genomes from related species
Example: Developed tools for the estimation of neutral substitution rates on a local scale
Study structure of rates
Study effect on evolution of genomic structure
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Software engineering
Software risk management and assessment
Probabilistic risk assessment
Software design methodology
Experimental verification of software design methodology effectiveness
Visual programming languages
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DNA tiling microarrays Massive data sets
Broad coverage of genome
Low signal/noise ratio
Want to extract statistically significant information to justify validation experiments in a wet lab
Seek collaboration from statisticians to develop appropriate statistics
Seek collaboration from computer scientists to effectively implement statistical and data processing algorithms
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Looking for collaboration on genomic sequence assembly and clustering
Work with expressed sequence tags (EST) from complementary DNA (cDNA) How trace a given set of ESTs back to their
original genes?
New technologies can now very quickly sequence enormous amounts of short pieces of cDNA Want computational tools to do correct
assembly and clustering
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Software development in C/C++/Fortran for numerical computation
Conversion of software for parallel computation
Application support for various physics and biophysics packages, e.g., ANSYS, Abaqus
Modeling and simulation of vascular systems
Geometric model generation
Flow solving
Data visualization
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Expertise is applied probability
Served on graduate committees in zoology
Helped graduate students with data analysis
Experience in
Analysis of variance
Markov chains
Hidden Markov Models
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Expertise in optimization and simulation of complex systems
Bioinformatics experience Sequencing by hybridization
Clustering the avian-flu viruses (with Henry Wan)
Working with Chun Liang (Botany) and CSA colleagues to cluster Expressed Sequence Tags (ESTs) to identify genes for conifers
Would like to hear from other biologists with similar research, e.g., use of ESTs for gene identification and regulation
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Has taught classes in introductory statistics, regression analysis, and time series analysis
Extensive experience applying statistics in business, social science, and natural science Time series analysis to study chemical concentrations
of stream flows into Acton Lake
Applications of regression techniques
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Scientific programming, especially C++ and MATLAB
Parallel programs on cluster
Graphical user interfaces (GUI) for programs
Mathematical modeling
Digital image processing
Basic knowledge of variety of mathematical techniques
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Works in Michael Kennedy’s lab
Seek collaboration and support for
Nuclear Magnetic Resonance (NMR) data
Use of principal component analysis (PCA)
Use of partial least squares discriminant analysis (PLS-DA)
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Installation and configuration of bioinformatics applications on the cluster
IT infrastructure planning and support -servers, network, storage, etc.
Scripting (writing programs for cluster) and help with cluster batch system
Database creation and advice on use
General support of cluster users
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Principal expertise Mathematical optimization (theory, algorithms,
software) Modeling of decision problems
Research interests Reformulating mathematical problems for efficiency Applications of optimization to data-fitting Parallel processing in optimization Optimal design of experiments
Areas of application (to date) Crystallography, statistics, hydrology, econometrics,
toxicology, engineering, ecology
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Knowledge of statistics useful in Microarray studies (separating signal from
noise, cluster analysis, missing data), image analysis
Clinical studies, forestry and wild life, public health
Specific statistical tools Bayesian hierarchical modeling and Markov
chain Monte Carlo (MCMC) algorithms
Spatial analysis (areal data and point-referenced data), including prediction and model checking
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